Novel anthropometric indicators of visceral obesity predict the severity of hyperlipidemic acute pancreatitis.

BACKGROUND: Obesity substantially contributes to the onset of acute pancreatitis (AP) and influences its progression to severe AP. Although body mass index (BMI) is a widely used anthropometric parameter, it fails to delineate the distribution pattern of adipose tissue. To circumvent this shortcoming, the predictive efficacies of novel anthropometric indicators of visceral obesity, such as lipid accumulation products (LAP), cardiometabolic index (CMI), body roundness index (BRI), visceral adiposity index (VAI), A Body Shape Index (ABSI), and Chinese visceral adiposity index (CVAI) were examined to assess the severity of AP. METHOD: The body parameters and laboratory indices of 283 patients with hyperlipidemic acute pancreatitis (HLAP) were retrospectively analysed, and the six novel anthropometric indicators of visceral obesity were calculated. The severity of HLAP was determined using the revised Atlanta classification. The correlation between the six indicators and HLAP severity was evaluated, and the predictive efficacy of the indicators was assessed using area under the curve (AUC). The differences in diagnostic values of the six indicators were also compared using the DeLong test. RESULTS: Patients with moderate to severe AP had higher VAI, CMI, and LAP than patients with mild AP (all P < 0.001). The highest AUC in predicting HLAP severity was observed for VAI, with a value of 0.733 and 95% confidence interval of 0.678-0.784. CONCLUSIONS: This study demonstrated significant correlations between HLAP severity and VAI, CMI, and LAP indicators. These indicators, particularly VAI, which displayed the highest predictive power, were instrumental in forecasting and evaluating the severity of HLAP.

Lactate enhances NMNAT1 lactylation to sustain nuclear NAD+ salvage pathway and promote survival of pancreatic adenocarcinoma cells under glucose-deprived conditions.

The aim of this study was to investigate the underlying molecular mechanism behind the promotion of cell survival under conditions of glucose deprivation by l-lactate. To accomplish this, we performed tissue microarray and immunohistochemistry staining to analyze the correlation between the abundance of pan-Lysine lactylation and prognosis. In vivo evaluations of tumor growth were conducted using the KPC and nude mice xenograft tumor model. For mechanistic studies, multi-omics analysis, RNA interference, and site-directed mutagenesis techniques were utilized. Our findings robustly confirmed that l-lactate promotes cell survival under glucose deprivation conditions, primarily by relying on GLS1-mediated glutaminolysis to support mitochondrial respiration. Mechanistically, we discovered that l-lactate enhances the NMNAT1-mediated NAD+ salvage pathway while concurrently inactivating p-38 MAPK signaling and suppressing DDIT3 transcription. Notably, Pan-Kla abundance was significantly upregulated in patients with Pancreatic adenocarcinoma (PAAD) and associated with poor prognosis. We identified the 128th Lysine residue of NMNAT1 as a critical site for lactylation and revealed EP300 as a key lactyltransferase responsible for catalyzing lactylation. Importantly, we elucidated that lactylation of NMNAT1 enhances its nuclear localization and maintains enzymatic activity, thereby supporting the nuclear NAD+ salvage pathway and facilitating cancer growth. Finally, we demonstrated that the NMNAT1-dependent NAD+ salvage pathway promotes cell survival under glucose deprivation conditions and is reliant on the activity of Sirt1. Collectively, our study has unraveled a novel molecular mechanism by which l-lactate promotes cell survival under glucose deprivation conditions, presenting a promising strategy for targeting lactate and NAD+ metabolism in the treatment of PAAD.

Rethinking industrial land-use in American rust cities towards sustainability based on a block-level model.

Urban land is a fundamental but scarce resource that carries intensive human socio-economic activities. The demographic decline and housing vacancy issues that emerged with de-industrialization have raised concerns regarding the sustainable utilization of urban land resources, particularly in the American Rust Belt region. In this context, a comprehensive analysis of industrial land use can offer valuable insights to support the sustainable planning of shrinking cities. However, existing urban land research exhibits insufficient resolution at the sectoral scale and impedes the evaluation of industrial land use efficiency within the urban context. To address this gap, we established an integrated land use estimation framework for economic sectors based on multi-source data, which enables the assessment of land use efficiency at a finer sectoral scale. The method was then applied to the city of Detroit, Cleveland, and Pittsburgh. The results demonstrate that the current industrial land mix in the three cities is dominated by service-providing industries, but the land usage by goods-producing sectors in these cities presents a relatively high level of efficiency. The Moran's I value indicates a clustered tendency for the main economic sectors. The land use area results reveal that Other Services occupies the most land area in Detroit (2.29 million m2) and Cleveland (2.04 million m2). While in Pittsburgh, Professional Scientific and Technical Services (1.44 million m2) is the largest. In terms of the economic output, Management of Companies and Enterprises is the most efficient sector in Detroit (20.28 thousand $/m2) and Cleveland (29.43 thousand $/m2), while Pittsburgh's Public Administration (11.73 thousand $/m2) is the most efficient. As many other cities in the world are about to enter the era of de-industrialization or low growth, the outcomes can also serve as a reference to guide their sustainable revitalization in line with the SDGs.

Country-specific net-zero strategies of the pulp and paper industry.

The pulp and paper industry is an important contributor to global greenhouse gas emissions1,2. Country-specific strategies are essential for the industry to achieve net-zero emissions by 2050, given its vast heterogeneities across countries3,4. Here we develop a comprehensive bottom-up assessment of net greenhouse gas emissions of the domestic paper-related sectors for 30 major countries from 1961 to 2019-about 3.2% of global anthropogenic greenhouse gas emissions from the same period5-and explore mitigation strategies through 2,160 scenarios covering key factors. Our results show substantial differences across countries in terms of historical emissions evolution trends and structure. All countries can achieve net-zero emissions for their pulp and paper industry by 2050, with a single measure for most developed countries and several measures for most developing countries. Except for energy-efficiency improvement and energy-system decarbonization, tropical developing countries with abundant forest resources should give priority to sustainable forest management, whereas other developing countries should pay more attention to enhancing methane capture rate and reducing recycling. These insights are crucial for developing net-zero strategies tailored to each country and achieving net-zero emissions by 2050 for the pulp and paper industry.

Machine learning for predicting the risk stratification of 1-5 cm gastric gastrointestinal stromal tumors based on CT.

BACKGROUD: To predict the malignancy of 1-5 cm gastric gastrointestinal stromal tumors (GISTs) by machine learning (ML) on CT images using three models - Logistic Regression (LR), Decision Tree (DT) and Gradient Boosting Decision Tree (GBDT). METHODS: 231 patients from Center 1 were randomly assigned into the training cohort (n = 161) and the internal validation cohort (n = 70) in a 7:3 ratio. The other 78 patients from Center 2 served as the external test cohort. Scikit-learn software was used to build three classifiers. The performance of the three models were evaluated by sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV) and area under the curve (AUC). Diagnostic differences between ML models and radiologists were compared in the external test cohort. Important features of LR and GBDT were analyzed and compared. RESULTS: GBDT outperformed LR and DT with the largest AUC values (0.981 and 0.815) in the training and internal validation cohorts and the greatest accuracy (0.923, 0.833 and 0.844) across all three cohorts. However, LR was found to have the largest AUC value (0.910) in the external test cohort. DT yielded the worst accuracy (0.790 and 0.727) and AUC values (0.803 and 0.700) in both the internal validation cohort and the external test cohort. GBDT and LR performed better than radiologists. Long diameter was demonstrated to be the same and most important CT feature for GBDT and LR. CONCLUSIONS: ML classifiers, especially GBDT and LR with high accuracy and strong robustness, were considered to be promising in risk classification of 1-5 cm gastric GISTs based on CT. Long diameter was found the most important feature for risk stratification.

Bio-straw or not? Determinants of consumption intention under the plastic straw ban.

A new plastic ban has banned the use of single-use non-degradable plastic drinking straws in China's food and beverage industry by the end of 2020. However, this has caused widespread discussion and complaints on social media. What are consumers' reactions and what factors influence consumers to choose bio-straws (substitutes for plastic straws) are unclear. Therefore, this research collected 4367 effective comments (177,832 words in total) on "bio-straws" from social media and extracted keywords based on grounded theory to generate questionnaires. Structural equation modeling was used to analyze the consumption intention and influencing factors of 348 consumers regarding the ban. The results indicate the following: (1) consumer opinion on straws can be summarized into five main categories, namely, consumers' user experience, consumer subjectivity, policy awareness, policy acceptance, and consumption intention; (2) consumer subjectivity, policy awareness, and policy acceptance directly affect consumption intention significantly, while user experience affects consumption intention indirectly; and (3) user experience and consumer subjectivity play significant roles in mediating these relationships. From the perspective of consumers, this study provides an important basis for policymakers to formulate single-use plastic alternative policies in the future.

Assessing life-cycle GHG emissions of recycled paper products under imported solid waste ban in China: A case study.

Changes of raw materials in China's recycled paper industry after the imported solid waste ban affect products' life-cycle greenhouse gas (GHG) emissions as well. This paper presented a case study of newsprint production with prior- and post-ban scenarios with life cycle assessment, including using imported waste paper (P0) and its three substitutions, i.e., virgin pulp (P1), domestic waste paper (P2), and imported recycled pulp (P3). The function unit is 1 ton of newsprint produced in China, and the study is conducted from cradle to grave which consists pulping and papermaking process, from raw material acquisition to manufacturing, with associated energy production and wastewater treatment, transport, and chemicals production. Our results showed that P1 holds the highest life-cycle GHG emission of 2724.91, followed by 2400.88 from P3. P2 has the lowest emission of 1619.27, only slightly lower than 1742.39 before the ban using route P0 (unit: kgCO2e/ton paper). Scenario analysis showed that current average life-cycle GHG emission for one ton of newsprint is 2049.33 kgCO2e, increased by 17.62 % due to the ban, while this number could be reduced to 12.22 % or even -0.79 % if switching from P1 to P3 and P2. Our study highlighted the importance of domestic waste paper as a promising way to reduce GHG emissions, which still has great potential to increase if with an enhanced waste paper recycling system in China.

An extensive pharmacological evaluation of novel anti-nociceptive and IL-6 targeted anti-inflammatory guaiane-type sesquiterpenoids from Cinnamomum migao H. W. Li through in-depth in-vitro, ADMET, and molecular docking studies.

Guaiane-type sesquiterpenoids are most prevalent in the genus Cinnamomum. Hence this study investigates the structures, anti-nociceptive and IL-6 targeted anti-inflammatory potential of three novels C-14 guaiane-type sesquiterpenoids and two new monoterpenoids, isolated from Cinnamomum migao. The structures were precisely confirmed and characterized through the modern chromatographic and spectroscopic techniques of HRESIMS, 1D NMR, 2D NMR, experimental circular dichroism (ECD), and calculated (ECD). Novel sesquiterpenoids 1 and 2 exhibited significant anti-inflammatory activities against the NO production and pro-inflammatory cytokines. Their IC50 values were determined as 9.52 and 13.42 µΜ against IL-6 mRNA, respectively. Similarly, subcutaneous injection of n-BuT and EA extracts showed a dose-dependent suppression of formalin-induced tonic biting/licking responses during the tonic antinociceptive phase. Furthermore, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis of guaiane-type sesquiterpenoids 1 and 2 displayed that both compounds have a high level of GIT absorption, with a high zone of safety for cardiac and hepatotoxicity and no inhibition of cytochromes. In addition, molecular docking and simulation studies strengthen the anti-inflammatory potential of sesquiterpene 2 which showed a good binding affinity with IL-6 protein. Overall the inclusive results showed that the extracts and newly isolated guaiane-type sesquiterpenoids from C. migao will provide new evidence for the traditional use of this species to treat inflammation and nociception.

Investigation on the mechanism of Ginkgo Folium in the treatment of Non-alcoholic Fatty Liver Disease by strategy of network pharmacology and molecular docking.

BACKGROUND: Ginkgo Folium has a favorable effect on non-alcoholic fatty live disease (NAFLD), but its mechanism remains unclear. OBJECTIVE: The aim of this study is to reveal the underlying mechanism of Ginkgo Folium in the treatment of NAFLD. METHODS: Ingredients of Ginkgo Folium and ingredients-related genes were collected from TCMSP database and SwissTargetPrediction website, respectively. Genecards database was used to obtain NAFLD-related genes. Next, the protein-protein interaction network and key ingredients-genes network were constructed via Cytoscape3.7.0. Based on the Metascape website, gene ontology function analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were carried out for key genes. Finally, molecular docking was performed to present the interaction between components and genes using AutoDock Vina 1.1.2. RESULTS: Eighteen active ingredients and 10 target genes were screened from Ginkgo Folium. AKT1, TNF, EGFR, PTGS2, MAPK8, PPAγ, APP, ESR1, HIFα and PPAα were considered as potential therapeutic targets. These target genes were mainly enriched in insulin resistance, HIF-1, adipocytokine and AMPK signaling pathways. Molecular docking results suggested that Ginkgo Folium active ingredients including luteolin-4'-glucoside, sesamin, luteolin, chryseriol, isorhamnetin and laricitrin showed strong binding capacities with AKT1. CONCLUSION: The study showed that multi-components in Ginkgo Folium interacted with AKT1 and regulated AKT-AMPK/HIF pathway to alleviate NAFLD. Our findings provided an essential role and basis for new anti-NAFLD drug discovery and further research on Ginkgo Folium.

Long non-coding RNA BC002811 Promotes Gastric Cancer Metastasis by Regulating SOX2 Binding to the PTEN Promoter.

There is increasing evidence that long non-coding RNAs (lncRNAs) are involved in the pathogenesis and progression of gastric cancer (GC), however, the underlying mechanisms remain poorly understood. In this study, we identified lncRNA BC002811 as a critical regulator of GC development and progression. BC002811 was upregulated in GC tissues and cell lines, and that high expression of BC002811 was indicative of a reduction in overall survival of GC patients. Our research reveals that BC002811 promoted GC cell proliferation, migration, invasion, and inhibition of apoptosis in vitro, as well as accelerated tumor growth and metastasis in vivo. We also found that BC002811 upregulated MMP2 and MMP9 and promoted GC cell metastasis partially through downregulating PTEN expression. BC002811 may act as a molecular decoy for the transcription factor SOX2, thereby inhibiting the transcription of PTEN by blocking SOX2 binding to the PTEN promoter. Our study advances the understanding of the role of BC002811 in the pathogenesis of GC and provides new molecular targets for therapeutic intervention against GC metastasis.

Construction of a metabolism-related gene prognostic model to predict survival of pancreatic cancer patients.

Pancreatic cancer (PC) is one of the most fatal malignant tumors, and is commonly diagnosed at an advanced stage with no effective therapy. Metabolism-related genes (MRGs) and immune-related genes (IRGs) play considerable roles in the tumor microenvironment. Therefore, an effective prediction model based on MRGs and IRGs could aid in the prognosis of PC. In this study, differential expression analysis was performed to gain 25 intersectional genes from 857 differentially expressed MRGs (DEMRGs), and 1353 differentially expressed IRGs, from The Cancer Genome Atlas database of PC. Cox and Lasso regression were applied and a five-DEMRGs prognostic model constructed. Survival analysis, ROC values, risk curve and validation analysis showed that the model could independently predict PC prognosis. In addition, the correlation analysis suggested that the five-DEMRGs prognostic model could reflect the status of the immune microenvironment, including Tregs, M1 macrophages and Mast cell resting. Therefore, our study provides new underlying predictive biomarkers and associated immunotherapy targets.

Stress response and influencing factors among fever outpatients and children's families during normalisation of the COVID-19 epidemic: A cross-sectional study.

AIM: To examine the demographic characteristics associated with stress response of fever outpatients and children's families during normalisation of the COVID-19 epidemic and to examine the relationship between stress response, coping style and resilience. DESIGN: Online cross-sectional study. METHODS: A total of 541 fever clinic participants from Yiwu, China, were recruited via WeChat from February to November 2021. Online self-administered questionnaires were used to collect data. Data were analysed using t-tests, one-way analyses of variance, Pearson's correlation analyses and multiple linear regression analyses. RESULTS: There were apparent physical and emotional responses among the fever outpatients, especially the adult patients. The main coping style was negative coping, and the degree of psychological resilience was low. Income, comorbidities, religious beliefs, tenacity, negative coping and positive coping were independent predictors of stress response.

Worm Generator: A System for High-Throughput in Vivo Screening.

Large-scale screening of molecules in organisms requires high-throughput and cost-effective evaluating tools during preclinical development. Here, a novel in vivo screening strategy combining hierarchically structured biohybrid triboelectric nanogenerators (HB-TENGs) arrays with computational bioinformatics analysis for high-throughput pharmacological evaluation using Caenorhabditis elegans is described. Unlike the traditional methods for behavioral monitoring of the animals, which are laborious and costly, HB-TENGs with micropillars are designed to efficiently convert animals' behaviors into friction deformation and result in a contact-separation motion between two triboelectric layers to generate electrical outputs. The triboelectric signals are recorded and extracted to various bioinformation for each screened compound. Moreover, the information-rich electrical readouts are successfully demonstrated to be sufficient to predict a drug's identity by multiple-Gaussian-kernels-based machine learning methods. This proposed strategy can be readily applied to various fields and is especially useful in in vivo explorations to accelerate the identification of novel therapeutics.

Triglycerides to high-density lipoprotein cholesterol (TG/HDL-C) ratio is an independent predictor of the severity of hyperlipidaemic acute pancreatitis.

BACKGROUND: The incidence of acute pancreatitis caused by hyperlipidaemia is increasing. A quick and easy diagnosis of the severity of hyperlipidaemic acute pancreatitis (HTGP) is important to improve patient prognosis and reduce mortality. Previous studies reported that insulin resistance (IR) is associated with acute pancreatitis. Our study aimed to investigate the correlation between the triglycerides to high-density lipoprotein cholesterol (TG/HDL-C) ratio and HTGP. METHODS: Patients' laboratory and clinical parameters were obtained from the institutional pancreatitis database. Univariate and multivariate logistic regression analyses were applied to evaluate the risk factors for the severity of HTGP and the efficacy of four clinical scoring systems: Ranson's Criteria, Acute Physiology and Chronic Health Evaluation II (APACHE II), the Bedside Index for Severity in Acute Pancreatitis (BISAP), and Marshall. RESULTS: Of 290 patients, 134 (46.2%) were diagnosed with moderately severe to severe HTGP. The TG/HDL-C ratio was higher in the moderately severe to severe HTGP subgroup than in the mild HTGP subgroup. Among the independent risk factors, such as amylase, albumin, aspartate transaminase (AST), systemic inflammatory response syndrome (SIRS), and TG/HDL-C ratio, the TG/HDL-C ratio had the highest area under the curve (AUC) (0.727, 95% CI, 0.571-0.701). In comparison with other clinical scoring systems, the TG/HDL-C ratio has a relatively preferable predictive ability. CONCLUSION: Our findings suggest that the TG/HDL-C ratio is positively correlated with HTGP severity and could be used as a simple indicator of severe HTGP.

Coupled impacts of climate and land use changes on regional ecosystem services.

Ecosystem services (ES) are key to maintaining sustainable regional development. Climate change and land cover and land use change (LULC) are one of the main factors leading to changes in regional ecosystem services. Existing studies have simulated regional ES changes under different future scenarios, providing valuable guidance for regional sustainable management. However, most studies focus on the effects of individual factors (LULC or climate change) on ES, paying insufficient attention to the coupled effects of the two elements. Yunnan Province is a biodiversity hotspot facing challenges in ES in the context of future climate change and rapid socio-economic development. In order to achieve sustainable management, policies must be developed in advance to address possible future ecological risks. In this study, we simulated the coupled effects of climate change and LULC on six types of ES using the SD, FLUS, and InVEST models. The scenario framework of shared socioeconomic pathways SSP245 and SSP585 was combined with LULC scenario dynamics to assess the changes of ES in 2030 and 2050, identifying sensitive areas and providing a scientific basis for local ecosystem management. In 2020, the eastern part of Yunnan Province was the coldspot area for all ES. Under the future scenarios, Yunnan Province's ES show different loss rates and distinct spatial heterogeneity. Future climate change and LULC changes have a more significant negative impact on water conservation and water quality purification. About 66% of its counties will become sensitive areas for water production services, and 37% of counties will endure reduced water purification functions by more than 50%. According to the analytical results, we then proposed several suggestions to improve regional ES management.

Camganoids A and B, two new sesquiterpenes with different carbon skeletons isolated from fruits of Cinnamomum migao.

Objective: To isolate and identify the undescribed compounds from the fruits of Cinnamomum migao and evaluate its nitric oxide inhibition potential. Methods: The chromatographic techniques of silica gel, Sephadex, and HPLC were used for isolation and purification of the compounds, while HR-ESI-MS, 1D NMR, 2D NMR, ECD, and X-ray diffraction techniques were used to characterize and confirm the isolated compounds. Moreover, the anti-inflammatory activity of the isolated compounds was carried out to check inhibitory potential against the production of nitric oxide with RAW264.7 cells stimulated by LPS. Results: Camganoid A (1), a novel sesquiterpene possessing an unprecedented skeleton, and camganoid B (2), containing a unique eight-membered sesquiterpene moiety with a new carbon skeleton, were isolated and identified from the fruits of C. migao. The absolute configurations of 1 and 2 were confirmed by single crystal X-ray diffraction and electronic circular dichroism (ECD) calculations. Among these compounds, compound 1 exhibited potent inhibitory activity against the production of nitric oxide with IC50 value of 4.59 µmol/L in RAW264.7 cells stimulated by LPS. Conclusion: The isolation of two new skeletons from the fruits part of C. migao possessed unique skeletons which have not been reported before.

Acute toxicological study: EZY-1 with potent therapeutic effects of idiopathic pulmonary fibrosis and its mechanisms.

EZY-1 is an antifibrosis peptide purified from Eucheuma. In this study, we explored the acute toxicology of EZY-1 and the signaling pathways involved in its antifibrotic role. The mouse model of pulmonary fibrosis was induced by bleomycin. Pathological changes in lung tissue could be effectively inhibited by EZY-1. Acute toxicity and cell proliferation tests indicated that EZY-1 had no apparent toxicity to mice and cells. We identified proteins that could bind directly to EZY-1 in vitro on the basis of liquid chromatography-tandem mass spectrometry and bioinformatics analysis. EZY-1 inhibited pulmonary fibrosis via Wnt/ß-catenin, transforming growth factor (TGF)-ß/Smad, phosphoinositide 3-kinase/protein kinase B/ mammalian target of rapamycin, and activator of transcription 3 and Janus kinase 2/signal transducer pathways. A transwell micropore experiment showed that EZY-1 could inhibit cell migration and invasion. Western blotting analysis on transforming growth factor-ß1 (TGF-ß1)-induced A549 pulmonary fibrosis cell model suggested that EZY-1 could downregulate p-Smad3 (Ser423/Ser425), Smad4, ß-catenin, vimentin, and N-cadherin expression. ELISA showed that EZY-1 could inhibit collagen-I secretion. EZY-1 alleviated idiopathic pulmonary fibrosis (IPF) through regulating TGF-ß/Smad pathways, epithelial-mesenchymal transition processes, and collagen secretion, which provides a potential foundation for theoretical development of EZY-1 as a potential drug against IPF. PRACTICAL APPLICATIONS: We isolated a new 16-amino-acid peptide derived from the polypeptide extract of Eucheuma, named EZY-1. In vitro and in vivo assays show peptide EZY-1 is safe. The EZY-1 peptide alleviates IPF at lower doses than pirfenidone. EZY-1 alleviated idiopathic pulmonary fibrosis (IPF) through regulating TGF-ß/Smad pathways, epithelial-mesenchymal transition (EMT) processes, and collagen secretion, which provides a theoretical basis for the development of EZY-1 as a potential drug against IPF.

Exports Widen the Regional Inequality of Health Burdens and Economic Benefits in India.

Both the ever-complex international and subnational supply chains could relocate health burdens and economic benefits across India, leading to the widening of regional inequality. Here, we simultaneously track the unequal distribution of fine particle matter (PM2.5) pollution, health costs, and value-added embodied in inter- and intranational exports for Indian states in 2015 by integrating a nested multiregional input-output (MRIO) table constructed based on EXIOBASE and an Indian regional MRIO table, Emissions Database for Global Atmospheric Research (EDGAR), the Community Multi-Scale Air Quality (CMAQ) model, and a concentration-response function. The results showed that the annual premature deaths associated with PM2.5 pollution embodied in inter- and intranational exports were 757,356 and 388,003 throughout India, accounting for 39% and 20% of the total premature deaths caused by PM2.5 pollution, respectively. Richer south and west coastal states received around half of the national Gross Domestic Product (GDP) induced by exports with a quarter of the health burden, while poorer central and east states bear approximately 60% of the health burden with less than a quarter of national GDP. Our findings highlight the role of exports in driving the regional inequality of health burdens and economic benefits. Therefore, tailored strategies (e.g., air pollution compensation, advanced technology transfer, and export structure optimization) could be formulated.

Differential gene expression analysis after DAPK1 knockout in hepatocellular carcinoma cells.

Background: The mechanism through which death-associated protein kinase 1 (DAPK1) causes hepatocellular carcinoma (HCC) progression remains unclear. In this study, we aimed to identify key proteins that were altered after DAPK1 knockout. Methods: Stable DAPK1 knockout HCC cell lines were established, then the differentially expressed genes (DEGs) of HCC were screened using the NetworkAnalyst database and enriched using the Metascape software. Protein-protein interaction networks (PPIs) were analyzed and visualized using the STRING database expansion. Results: In total, 732 differentially expressed genes were identified, including 415 upregulated genes and 317 downregulated genes. Through Cytoscape software scoring, 10 pivotal genes were found to be closely related to changes in DAPK1 expression; Kininogen-1 (KNG1), Complement C3 (C3), Metalloproteinase inhibitor 1 (TIMP1), and Alpha-2-HS-glycoprotein (AHSG) were the most strongly associated with DAPK1 expression changes. Moreover, western blot analysis results revealed that changes in the levels of proteins encoded by the four key genes after DAPK1 knockout were consistent with those seen in the database screening. Conclusions: These results provide a direction for further studies on the DAPK1 gene and on the mechanism through which DAPK1 leads to hepatocellular carcinoma development.

Fabrication of Nb2 O5 /Carbon Submicrostructures for Advanced Lithium-Ion Battery Anodes.

Nb2 O5 possesses superior fast Li+ storage capability for LIB anodes, benefiting from its fast pseudocapacitive behavior and low volumetric change within the cycling processes. However, the poor electric conductivity for Nb2 O5 restricts its reaction kinetics and rate property. Herein, Nb2 O5 /carbon (C) submicrostructures are fabricated by solvothermal method followed by calcination process. The Nb2 O5 /C submicrostructures exhibit outstanding rate behavior and cyclic performance (332 (194) mAh g-1 after 1000 cycles at 1 (5) A g-1 ). The superior electrochemical property is attributed to the distinctive structure for Nb2 O5 /C submicrostructures, in which Nb2 O5 nanoparticles uniformly distributed within Nb2 O5 /C composite can protect Nb2 O5 nanoparticles from agglomeration, and the porous carbon matrix can enhance electron/ion conductivity. This work furnishes a novel strategy for fabricating Nb2 O5 /C submicrostructures with superior Li+ storage performance, which can be potentially used to design other metal oxide/C submicrostructures for second battery anode.